In this work, we present the results of a rockfall trajectory study performed on the south-western slope of Mt. Catiello (Sorrento Peninsula, southern Italy). Such a study develops within a multi-methodological approach which integrates different types of remote sensing data and techniques. Specifically, ground-truth data (e.g., rock mass geo-structural information, rock block inventory) were generated by geologically-supervised interpretations of high-resolution virtual outcrop models (VOMs). These data were then used for reconstructing the in-situ fractured rock mass attributes of the Mt. Catiello peak, as provided by a Discrete Fracture Network (DFN) model, and to prepare the subsequent numerical simulations of rockfall trajectories. The resulting rockfall scenarios are consistent with the ground-truth data, both in terms of size and spatial distribution. Thus, we believe that the proposed approach can be effectively applied to other areas, characterized by similar geological features but higher levels of exposure and vulnerability.

在这项工作中，我们展示了在 Mt. Catiello（意大利南部索伦托半岛）西南坡进行的落石轨迹研究的结果。这样的研究是在综合不同类型的遥感数据和技术的多方法方法中发展的。具体而言，通过高分辨率虚拟露头模型 (VOM) 的地质监督解释生成地面真实数据（例如，岩体地质结构信息、岩块库存）。这些数据随后被用于重建由离散断裂网络 (DFN) 模型提供的 Mt. Catiello 峰的原位断裂岩体属性，并准备随后的落石轨迹数值模拟。由此产生的落石场景与地面真实数据一致，无论是规模还是空间分布。因此，我们相信所提出的方法可以有效地应用于其他具有相似地质特征但暴露程度和脆弱性更高的地区。